Natural Language Processing
Research Associate in Natural Language Processing
|Closing date: 12th November 2018||Job reference: UOS020630|
The Natural Language Processing Research Group , established in 1993 , is one of the largest and most successful language processing groups in the UK and has a strong global reputation.
Natural Language Processing (NLP) is an interdisciplinary field that uses computational methods:
Follow us on Twitter @SheffieldNLP
The group's research interests fall into the broad areas of:
Information Access: Building applications to improve access to information in massive text collections, such as the web, newswires and the scientific literature. Subtopics include: information extraction, text mining and semantic annotation, question answering, summarization.
Language Resources and Architectures for NLP: Providing resources - both data and processing resources - for research and development in NLP. Includes platforms for developing and deploying real world language processing applications, most notably GATE, the General Architecture for Text Engineering.
Machine Translation: Building applications to translate automatically between human languages, allowing access to the vast amount of information written in foreign languages and easier communication between speakers of different languages.
Human-Computer Dialogue Systems: Building systems to allow spoken language interaction with computers or embodied conversational agents, with applications in areas such as keyboard-free access to information, games and entertainment, articifial companions.
Detection of Reuse and Anomaly: Investigating techniques for determining when texts or portions of texts have been reused or where portions of text do not fit with surrounding text. These techniques have applications in areas such as plagiarism and authorship detection and in discovery of hidden content.
Foundational Topics: Developing applications with human-like capabilities for processing language requires progress in foundational topics in language processing. Areas of interest include: word sense disambiguation, semantics of time and events.
The NLP group's research has received support from: the EU's Framework Programmes (Frameworks 4, 5, 6 and 7) as well as Horizon 2020 and the European Research Council, the UK Research Councils (EPSRC, BBSRC, MRC and AHRC) and various governmental and industrial sponsors, including GlaxoSmithKline and IBM.
These are currently the members of NLP group. Click on a name to see a home page.
Click on a year to read the news stories
29 November 2018 - Adam Tsakalidis (University of Warwick)
2018 - 2019
NLP Reading Group
The target audience is all the members of the NLP group and other possible interested participants.
The meeting will take place weekly for one hour usually on Tuesdays from 11-12pm.
The meetings of the group will be informal and no necessary preparation will be required with the exception of the moderator reading the current paper and the rest having at least a brief overview of it.
Tuesday 12 June 2018
Chelsea Finn, Pieter Abbeel, Sergey Levine, ICML 2017
Tuesday 10 April 2018
Shen, T; Lei, T; Barzilay, R; Jaakola, T.
Tuesday 3 April 2018
Zhengli Zhao, Dheeru Dua and Sameer Singh
Tuesday 20 February 2018
ACL Paper submission feedback session
Tuesday 13 February 2018
Edouard Grave, Moustapha Cisse & Armand Joulin
Tuesday 6 February 2018
Alessandro Raganato, Claudio Delli Bovi & Roberto Navigli
Tuesday 30 January 2018
Tim Rocktäschel & Sebastian Riedel
Tuesday 23 January 2018
Unsupervised Learning of Universal Sentence Representations from NLI Data.
Tuesday 28 November 2017
Melvin Johnson, Mike Schuster, Quoc V. Le, et al.
Tuesday 14 November 2017
Grzegorz Chrupała, Lieke Gelderloos & Afra Alishahi
Tuesday 7 November 2017
Hui Lin & Jeff Bilmes
Tuesday 31 October 2017
Nan Duan, Duyu Tang, Peng Chen & Ming Zhou
Tuesday 24 October 2017
Roee Aharoni & Yoav Goldberg
Tuesday 17 October 2017
Hao Cheng, Hao Fang, Mari Ostendorf
Tuesday 10 October 2017
Pang Wei Koh, Percy Liang; Published in Proceedings of International Conference on Machine Learning, 2017
Tuesday 3 October 2017
Omer Levy, Minjoon Seo, Eunsol Choi and Luke Zettlemoyer
Tuesday 19 September 2017
Tuesday 29 August 2017
Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell
Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3309-3318, 2017.
Tuesday 22 August 2017
Split and Rephrase, Accepted for EMNLP 2017
Shashi Narayan, Claire Gardent, Shay B. Cohen and Anastasia Shimorina
Tuesday 15 August 2017
Attention Is All You need
Tuesday 8 August 2017
Dzmitry Bahdanau, Tom Bosc, Stanisław Jastrzębski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio
Tuesday 1 August 2017
Learning to Generate Textual Data, EMNLP 2016
Tuesday 11 July 2017
Yusuf Aytar, Carl Vondrick, Antonio Torralba
Tuesday 4 July 2017
Xingxing Zhang, Mirella Lapata
Tuesday 27 June 2017
Junhua Mao, Jonathan Huang, Alexander Toshev, Oana Camburu, Alan Yuille, Kevin Murphy
Tuesday 20 June 2017
Understanding the BPE algorithm
Tuesday 13 June 2017
Ron J. Weiss, Jan Chorowski, Navdeep Jaitly, Yonghui Wu, Zhifeng Chen
Tuesday 6 June 2017
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin
Tuesday 30 May 2017
Wang Ling, Dani Yogatama, Chris Dyer, Phil Blunsom
Tuesday 9 May 2017
Tuesday 6 May 2017
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin
Tuesday 2 May 2017
Tuesday 25 April 2017
Mert Kilickaya, Aykut Erdem, Nazli Ikizler-Cinbis, Erkut Erdem
Tuesday 18 April 2017
Neural Tree Indexers, EACL2017
Tuesday 11 April 2017
Tuesday 4 April 2017
Tuesday 28 March 2017
Tuesday 21 March 2017
Tuesday 14 March 2017
Kim et al. (2016): Examples are not Enough, Learn to Criticize! Criticism for Interpretability, NIPS 2016
Tuesday 7 March 2017
Kris Cao and Stephen Clark
Tuesday 28 February 2017
Tuesday 21 February 2017
Tuesday 14 February 2017
by Fabio Petroni, Luciano Del Corro and Rainer Gemulla
Tuesday 7 February 2017
Takeru Miyato, Andrew, M.Dai, Ian Goodfellow
Tuesday 31 January 2017
Tim Vieira and Jason Eisner
Tuesday 24 January 2017
Oriol Vinyals, Charles Blundell, Tim Lillicrap, Koray Kavukcuoglu, Daan Wierstra
Tuesday 17 January 2017
Learning Structured Predictors from Bandit Feedback for Interactive NLP. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL). Berlin, Germany
Artem Sokolov, Julia Kreutzer, Christopher Lo, Stefan Riezler
Tuesday 13 December 2016
Marc Dymetman, Guillaume Bouchard, Simon Carter
Tuesday 6 December 2016
Rong Ge, Jason D. Lee, Tengyu Ma
Tuesday 29 November 2016
Compositional Semantic Parsing on Semi-Structured Tables
Tuesday 22 November 2016
Minimum Risk Training for Neural Machine Translation
Tuesday 15 November 2016
Generation from Abstract Meaning Representation using Tree Transducers
Tuesday 1 November 2016
Visual Representations for Topic Understanding and Their Effects on Manually Generated Labels Transactions of the Association for Computational Linguistics, 2016.
Tuesday 25 October 2016
Tuesday 11 October 2016
A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
Tuesday 4 October 2016
Ultradense Word Embeddings by Orthogonal Transformation
Tuesday 7 June 2016
Not All Character N-grams Are Created Equal: A Study in Authorship Attribution.
Tuesday 31 May 2016
Riedel, S., Yao, L., McCallum, A., & Marlin, B. M. (2013)
Tuesday 10 May 2016
Tuesday 3 May 2016
A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing
Tuesday 22 April 2016
Sequence Level Training with recurrent Neural Networks
Tuesday 22 March 2016
"Distributed Representation of Sentences and Documents"
Tuesday 8 March 2016
AutoExtend: Extending Word Embeddings to Embeddings for Synsets and Lexemes
Tuesday 23 February 2016
From Word Embeddings To Document Distances
Tuesday 16 February 2016
Tuesday 9 February 2016
Tuesday 25 January 2016
Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks
Tuesday 19 January 2016
Tuesday 12 January 2016
Tuesday 8 December 2015
Using Discourse Structure Improves Machine Translation Evaluation.
And here are the author's slides
Tuesday 1 December 2015
Practical Bayesian Optimization of Machine Learning Algorithms Advances in Neural Information Processing Systems, 2012
Related presentations/lecture slides:
My reading group presentation slides
Tuesday 24 November 2015
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks ACL 2015
Additional resource about LSTM: "Anyone Can Learn To Code an LSTM-RNN in Python"
Tuesday 17 November 2015
More details on auto encoders for unsupervised pre-training:
Tuesday 10 November 2015
Tuesday 3 November 2015
Tuesday 27 October 2015
might help to read this NLP primer
Tuesday 20 October 2015
Teaching Machines to Read and Comprehend. NIPS 2015.
Slides (presented at LXMLS)
NAACL 2013 Tutorial "Deep Learning without Magic"
EMNLP 2014 Tutorial "Embedding Methods for NLP"
Entailment with Neural Attention (better description of attention models than in the NIPS paper in my opinion)
Tuesday 13 October 2015
A large annotated corpus for learning natural language inference. Proceedings of EMNLP 2015.
Should compare this to work on (multilingual) textual similarity
Funded Research Projects
|Resources||Group member resources|